Object Attribute Driven Super Resolution Encoding
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Solution Overview
Problem
Current Super Resolution Encoding (SRE) modes lack the ability to render content within the same page using different sets of bit patterns based on image attributes, leading to color distortion and low resolution in printed images.
Innovation Solution
A system that identifies object families and attributes in an input image, determines the appropriate reference table or ratio-based tag, and uses these to encode high resolution objects into a reduced bit form, allowing for different sets of bit patterns to be used for decoding and rendering based on object attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a single set of bit patterns is used for rendering on a per print job and/or on a page basis irrespective of the image content attributes, then the rendering process is simple and fast, but color distortion and low resolution occur in the rendered images
Solution Approach 1:
The patent applies local quality by associating different sets of bit patterns with different objects based on their attributes (size, type, language). Each object receives a customized bit pattern set tailored to its specific characteristics, enabling high-quality rendering for each object type (e.g., text, line art, images) while maintaining overall system efficiency through automated attribute-based classification.
2Manufacturing precision
If high resolution binary or bit map color image data is rendered at super resolution (e.g., 2400 spi), then perceptible jaggedness in text and line art is reduced or avoided, but data storage and transmission requirements increase significantly (up to two gigabytes or more per page)
Solution Approach 1:
The patent extracts only the essential information needed for high-quality rendering by using object attribute tags (size, type, language) to identify appropriate bit pattern sets. Instead of storing and transmitting complete high-resolution binary image data, the system transmits compressed representation data with associated tags, extracting the minimal necessary information to achieve super resolution rendering without the full data burden.
3Adaptability or versatility
If traditional SRE modes are used without object attribute differentiation, then encoding and decoding is straightforward, but the ability to render different content types (low point v. high point data, Kanji v. English characters) with appropriate bit patterns is lost
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple sets of bit patterns tailored to different object types (text, line art, images, specific languages like Kanji or English). During encoding, object attributes are analyzed and the appropriate pre-prepared bit pattern set is selected and associated with the object. This preliminary organization of bit pattern sets by object characteristics enables adaptable rendering without complex real-time generation, balancing versatility with manageable complexity.
Data Source
AI summary
Systems and methods for encoding high resolution data associated with a relatively large number of bits to an encoded form having a relatively reduced number of bits. The method includes, by a processor: receiving an input image comprising one or more high resolution objects. The method further includes, for each of the one or more high resolution objects: identifying an object family for that object and determining whether a reference table exists for the object family. If a reference table exists for the object family, the method includes determining a size of that object, and identifying a tag based on the size. The method also includes encoding that object to form an encoded object having a relatively reduced number of bits, associating the identified tag with the encoded object, and saving the encoded object.